Job title: Project Lead – RWE Data Analytics

Location: Barcelona

% of travel expected: Travel required as per business need

Job type: Permanent and Full time

About the job

Our Team:

Sanofi Business Operations is an internal Sanofi resource organization based in India and is setup to centralize processes and activities to support Specialty Care, Vaccines, General Medicines, CHC, CMO, and R&D, Data & Digital functions. Sanofi Business Operations strives to be a strategic and functional partner for tactical deliveries to Medical, HEVA, and Commercial organizations in Sanofi, Globally.

Main responsibilities:

Contribute to the growth of General Medicine’s real-world evidence capability, including real world evidence (RWE) to support studies and projects across the franchises motivated by business needs; work closely with the Medical, Market Access, HEOR, and Commercial team to maximize the value of our portfolio of priority assets worldwide; unique opportunity for a data scientist and/or epidemiologist to join a motivated and experienced research team in an innovative working environment to address key tasks in health and social care surrounding CV disease and diabetes; work collaboratively to create high quality innovative analytical products, can benefit from a wealth of in-house databases, study platforms, and analytic tools, and from external partnerships with academic and governmental institutions.

• People:
• (1) Work together with RWE team to support projects across the franchises motivated by business needs
• (2) Work closely with the Medical, Market Access, HEOR, and Commercial team to maximize the value of our portfolio of priority assets worldwide
• (3) Work collaboratively within Medical and across functions, with clients and external collaborators
• (4) Functionally reports to the Head of the Real-World Evidence team
• Process:
• (1) Work together and lead research analytical projects, including project conceptualization and design
• (2) Lead analysis of healthcare data, including clinical trial datasets, transactional claims, and electronic health records, using established and novel statistical and analytical techniques
• (3) Generate rapid response analyses for cross-functional stakeholders
• (4) Lead or contribute to drafting and reviewing technical and study reports, manuscripts for publishing in high-impact peer-reviewed journals, and abstracts and presentations for international conferences
• (5) Actively manage project activity and timelines
• (6) Internally advise your colleagues in the Health Economics, Commercial, and Medical franchises on your areas of technical and research expertise as directed by your supervisor
• (7) Communicate complex concepts and interpretation of analysis and findings to different audiences, including health economists, clinicians, policy makers, and health systems
• (8) Represent the team at external meetings
• (9) Validate and secure access to third-party healthcare data-sets
• Customer:
• (1) Deliver research and contributes to the RWE strategic direction for General Medicines

About you

• Experience: 7 - 10 years in public health, biotechnology and/or pharmaceutical industry; Strong healthcare data analysis expertise, expertise in data analysis techniques, and good understanding of healthcare datasets (EHR, Claims, RCTs), and data structures; Expertise in use of statistical methods to investigate real-world problems (e.g., data modelling, time to event analysis); Advanced experience in preparing, analysing, and managing large healthcare datasets in interventional and/or non-interventional studies; Experienced in interpreting and presenting complex analyses and findings; Experienced in interpreting and presenting complex analyses and findings
• Soft skills: Integrity; Analytic excellence; Excellent written and oral communication skills; ability to communicate complex topics and data results in a concise and precise manner; High level of self-awareness; Ability to cooperate cross-functionally; Problem-solving and creative thinking skills; Enjoys working independently, flexibly and as part of a team on multiple projects; Enthusiastic and professional approach to working with colleagues, clients, and external collaborators
• Technical skills: R, Python, SQL, advanced Microsoft Excel using Visual Basic for Application, SAS Education: Masters or PhD in a quantitative subject (e.g., computer science, data science, statistics, mathematics, biostatistics, biomedical engineering, epidemiology) or equivalent combination of education, training, and experience
• Languages: Excellent knowledge of English language (spoken and written)

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